<!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. -->
tf_bert_uncased_emotion_detection2
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0621
- Train Accuracy: 0.9701
- Validation Loss: 0.1144
- Validation Accuracy: 0.9385
- Epoch: 3
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
Trainig data : emotion
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- optimizer: {'name': 'Adam', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 6000, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|---|---|---|---|---|
| 0.3768 | 0.8637 | 0.1393 | 0.9345 | 0 |
| 0.1185 | 0.9426 | 0.1309 | 0.9380 | 1 |
| 0.0785 | 0.9583 | 0.1144 | 0.9385 | 2 |
| 0.0621 | 0.9701 | 0.1144 | 0.9385 | 3 |
Framework versions
- Transformers 4.24.0
- TensorFlow 2.9.2
- Datasets 2.7.0
- Tokenizers 0.13.2
